Vélez, Miguel González

e20518 Background: Gut microbiome dysbiosis is correlated with graft-versus-host disease (GVHD) in allogeneic stem cell transplant (allo-SCT) patients. In the allo-SCT population, antibiotics have been associated with increased risk for GVHD mortality and relapse due to loss of gut obligate anaerobes . It has been shown that antibiotics may negatively impact the efficacy of checkpoint inhibitors for patients with solid tumors. Based on these studies, we performed a retrospective analysis to determine if antibiotic treatment affects outcomes of multiple myeloma (MM) patients after autologous SCT (ASCT). Methods: This is a single institution retrospective study at Hackensack University Medical Center. A list of consecutive MM patients treated from 1/2012 to 12/2015 was obtained and an electronic medical record review of the first 217 who received ASCT was performed. Baseline characteristics, treatment history, transplant course and antibiotic treatment (including β-lactams, fluoroquinolones, macrolides, metronidazole, and vancomycin) were reviewed. Prophylactic antibiotics were excluded. Response was defined using the IMWG criteria. Median progression free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Log rank tests were used to compare the difference in survival between stratified groups. The LASSO cox regression analysis method was used for multivariate analyses of PFS and OS. Results: Of the 217 patients, 205 patients were available for analysis. Median age at ASCT was 61. β-lactams were associated with decreased median PFS (1.95 vs 4.77 years (yrs), p < 0.01) and decreased median OS (7.51 vs 13.45 yrs, p = 0.01). Multivariate analysis adjusting for lasso-selected age, gender, complete remission (CR) after ASCT, and ISS demonstrated independent progression risk associated with β-lactam use (HR = 2.00, 95% CI, 1.28–3.12, p < 0.01). β-lactams were associated with worse OS in multivariate analysis adjusting for lasso-selected age, gender, CR after ASCT and high risk cytogenetics (HR = 1.89, 95% CI, 1.07–3.40, p = 0.03). Conclusions: In this preliminary study, β-lactams predicted for decreased PFS and OS compared to patients who did not receive β-lactams in MM patients undergoing ASCT. The study was limited by its retrospective nature but demonstrates one of the first evaluations of antibiotic effect on the ASCT population in MM. Prospective studies evaluating the impact of antimicrobials on patient outcomes and the gut microbiome are ongoing.

Background: Serum folate (SF), vitamin B12 (B12), and iron deficiencies (def) are common causes of nutritional anemias. These deficiencies are usually multifactorial, with nutritional and non-nutritional factors playing a role. SF, B12, and iron levels are usually ordered in the setting of anemia, and malnutrition with or without neurologic symptoms. Since folic acid fortification, the prevalence of SF def in the United States (US) is <1% in the general population. B12 def and iron def range between 6-12%, and 1-11% respectively depending on the population studied. The prevalence of nutritional anemias secondary to SF, B12, and/or iron def by racial groups in the US is poorly studied, and most data available focuses on non-Hispanic whites (NHW). We aimed to determine the prevalence of anemia secondary to nutritional deficiencies by racial groups in the US. Methods: We performed a retrospective analysis of patients with SF, B12 and iron levels at Mayo Clinic Arizona between 01/2010 and 10/2018. Race was classified according to the NIH criteria. Normal laboratory values were determined according to our lab reference and the US National Health and Nutrition Examination Survey (NHANES) III. SF levels (mcg/Lt) were defined as deficient <4, normal ≥4.0, and excess ≥20. B12 levels (ng/L) as deficient <150, borderline 150-400, normal >400-900, and excess ≥900. Iron def was determined by ferritin levels (mcg/L) as low <24, normal 24-336, elevated ≥336 for men, low <11, normal 11-307, elevated ≥307 for women. Demographics and clinical variables were compared between groups by chi-square test for frequency data or Kruskal Wallis rank-sum test for continuous variables. Multivariable logistic regression was used for a sample-level analysis adjusting for age and gender and using NHW as a reference group. Results: A total of 79,926 SF, 107,731 B12, and 39,827 ferritin samples from 67,683 patients were analyzed. Demographics and sample analysis are presented in Table 1. In the sample-level analysis, 23,008 (25%) had anemia with higher prevalence in the American Indian/Alaskan Native (AI/AN) 49% and African Americans (AA) 43% (p<0.001). The prevalence of SF def was 446/79,926 (0.6%), B12 def 1,548/107,731 (1.4%), and iron def 5,212/39,827 (13.1%). 23 had concomitant SF and B12 deficiency, 25 SF and iron def, and 144 B12 and iron def. The SF def prevalence by racial groups was: AI/AN 11 (1.9%), AA 19 (1.1%), NHW 378 (0.6%), Hispanic 28 (0.5%), Asian 4 (0.2%). The B12 def prevalence by racial groups was: Asian 89 (3.4%), NHW 1,274 (1.4%), Hispanic 87 (1.3%), AA 30 (1.3%), AI/AN 10 (1.3%). Iron def prevalence by racial groups: AI/AN 71 (20.5%), Asian 198 (17.6%), AA 180 (16.9%), Hispanic 432 (15.6%), NHW 4,161 (12.4%). In the multivariate sample-level analysis, the presence of anemia was higher in the AI/AN (OR: 4.51, 95%CI: 3.70-5.49, p<0.0001), AA (OR 3.34, 95%CI: 2.99-3.74, p<0.0001), Asian (OR 1.52, 95%CI: 1.35-1.73, p<0.0001) and Hispanic racial group (OR 1.41, 95%CI: 1.30-1.52, p<0.0001). SF def was more common in the AI/AN (OR: 2.94, 95%CI: 1.60-5.39, p<0.001) and AA (OR 1.71, 95%CI: 1.08-1.53, p=0.02). B12 def was more common in the Asian racial group (OR: 2.535, 95%CI: 20.03-3.16, p<0.0001). Iron def was more common in the AI/AN (OR: 1.62, 95%CI: 1.21-2.17, p<0.001), Asian (OR 1.31, 95%CI: 1.0-1.57, p=0.003), and AA racial group (OR 1.26, 95%CI: 1.05-1.52, p=0.001). Conclusions: In our cohort, we show that despite the low prevalence of nutritional anemias in the US, racial disparities exist. Major differences were observed in the prevalence of anemia, SF def and iron def especially among AI/AN and AA. These differences may be linked to medical causes, nutritional practices and other social determinants of health. More research regarding the causes of these disparities and its clinical implications on a population level are needed. Targeted strategies to improve folate, B12 and iron intake in at higher risk populations could decrease adverse outcomes and decrease healthcare disparities caused by nutritional anemias. T able 1. Sample-level comparison by race Disclosures No relevant conflicts of interest to declare.

e14132 Background: The use of PD-1 inhibitors (PD1) has been limited due to the lack of prognostic markers of response. Previous studies have suggested that indirect inflammatory markers such as neutrophil lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) may correlate with response to treatment and improved survival. We sought to evaluate the impact NLR and PLR in a real world cohort of patients (pts) with advanced solid tumors treated with PD1. Methods: Records of all pts treated with PD1 between 2011-2017 at the John Theurer Cancer Center were reviewed. NLR and PLR were registered at baseline and longitudinally. We dichotomized as low (lNLR/lPLR), and high (hNLR ≥5/hPLR ≥160). Univariate logistic regression and Cox proportional hazards were used for progression free survival (PFS), and overall survival (OS). Landmark analyses were performed at cycles 2 (C2), and 5 (C5). Results: 178 pts received 1131 cycles of PD1. Median age was 65 (range 24-93); 43% were female. ECOG was ≥1 for 85%. 142 pts (80%), and 89 (50%) received ≥2C and ≥5C respectively. In univariate analyses, baseline hNLR and hPLR were independently associated with inferior OS (median 7.8 vs 18.3 months; HR 1.77, 95% CI 1.21-2.43; p = 0.004), ) and (median 6.4 vs 15.6 months; HR 1.42, 95% CI 1.09-2; p = 0.04) respectively. On landmark analyses, lNLR and lPLR were associated with longer PFS and OS at 2C, and 5C. Longitudinally, lNLR and lPLR correlated with response rate; NLR decreased by 0.08 (95% CI: -0.19 to -0.04; p = 0.03) and PLR by 17 (95% CI: -29 to -14; p = 0.07) per month in responders compared with non-responders. hNLR or hPLR did not correlate with increase in autoimmune toxicities. Conclusions: hNLR, hPLR are adversely prognostic markers in pts receiving PD1 inhibitors in a “real world cohort”. These markers correlate with a longitudinal response and may help predict response. Further prospective studies are needed to determine their utility in decision making during treatment.

Abstract Background: Multiple myeloma (MM) accounts for approximately 1% of all cancers and 10% of hematologic malignancies in the United States (U.S.). MM occurs in all races, but the incidence in African Americans is two to three times higher than in non-Hispanic whites. MM is also slightly more frequent in men than women (1.4:1). Many clinical trials lack appropriate representation of specific patient populations, limiting the generalizability of the evidence obtained. Therefore, we determined the representation of ethnic minorities, the elderly, and women in MM clinical trials. Methods: Enrollment data from all therapeutic trials reported as completed in clinicaltrial.gov from 2000 to 2016 were analyzed. Clinical trials including other hematologic malignancies and with recruitment outside of the U.S. were excluded. Enrollment fraction (EF) was defined as the number of enrollees divided by the 2013 SEER database MM complete prevalence. Chi-square test was used to estimate differences in categorical data. Results: Out of 177 MM clinical trials (CT), 78 (44%) reported ethnicity with a total of 12,055 enrollees. Regarding enrollees' ethnic composition, 84% were non-Hispanic White (NHW), 8.6% African American (AA), 2.8% Asian, 1.8% Hispanic, and 0.1% Native American/Alaskan Indian. Out of those 78 CT, 52 (66%) were phase II, 15 (19%) phase III, and 11 (14%) phase I. Most of the results were published from 2012 to 2016 (74%). Forty-six (59%) trials were sponsored by industry, 7 (9%) by NCI, and 25 (32%) were investigator initiated. Participation in CT varied significantly across ethnic groups, NHW were more likely to be enrolled in CT (EF of 0.23) than AA (EF of 0.08, p &lt; 0.0001) and Hispanics (EF of 0.05, p&lt; 0.0001). Males had a higher recruitment rate than females (58% vs. 42%), but this could be explained by the higher incidence of MM in males. Enrollees' median age was 62 years. Younger patients (&lt; 65 years) were more likely to be enrolled in CT than the elderly (66% vs. 34%, p&lt;0.0001). Industry-sponsored trials were less likely to recruit AA compared with investigator-initiated trials (7.6% vs. 12%, p&lt;0.01). Conclusions: Despite the higher incidence of MM in African Americans and the elderly, the former only represented 8.6% of the study participants and 66% of these were less than 65 years of age; therefore, we are lacking data in the tolerability of these new agents in our aging MM population. We also observed that industry studies were less likely to recruit AA patients. Collaborations between investigators, sponsors, and the community are necessary to increase our minority and elderly patients' access to clinical trials. Citation Format: Narjust Duma, Miguel Gonzalez Velez, Jesus Vera-Aguilera, Richardo Parrondo, Veronica Mariotti, Jonas Paludo, Yucai Wang, Ronald Go, Alex Adjei. Diversity in multiple myeloma clinical trials [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr A27.

594 Background: Given the heterogeneity of gastrointestinal cancers (GICs), molecular profiling is becoming part of the standard of care for many solid tumors. The aim of this study was to evaluate the molecular profile of patients (pts) with GICs using a multiplatform profiling tool and to assess how the pattern of detected molecular alterations could guide clinical decision-making in these tumors. Methods: We retrospectively analyzed samples of 85 pts with GICs via a multiplatform profiling service (Caris Life Sciences, Phoenix, AZ) in order to evaluate clinically relevant genomic alterations (CRGAs) and clinically relevant biomarker expression (CRBs) in GICs. Results: A total of 85 pts with GICs were analyzed. 45 (53 %) were males and 40 (47%) were females. Tumors were colorectal 43 (51%), pancreatic 11 (13%) esophageal 11 (13%) gastric 8 (9%), hepatobiliary 8 (11%), anal canal 3 (4%), and small intestine 1 (1%). 80 cases (94%) had adequate sample for profiling. CRGAs were identified in 71 cases (89%) with a median of 3 CRGAs in the cohort. The most commonly detected CRGAs were TP53 45 (56%), APC 35 (44%), KRAS 32 (40%), ATM 14 (18%) and PTEN 5 (6%). The median number of CRBs was 9 and high expression levels were seen of mismatch repair biomarkers (MLH1, MSH2, MSH6, PMS2) in 45 (56%), TOPO1 in 44 (55%), PTEN in 27 (34%), TOP2A in 20 (25%), ERCC1 in 19 (24%), and both TS and TUBB3 in 17 (21%). Based on actionable CRGAs and CRBs, 94% of pts matched at least one FDA approved treatment with proven clinical benefit, with a median of 4 available therapies per pt. In addition, there was a median of 189 chemotherapy and 64 targeted therapy clinical trial opportunities available for these pts given the molecular blueprint of their GICs. Conclusions: Multiplatform molecular profiling identified a high frequency of actionable CRGAs and CRBs in GIC pts. This approach has the potential to aid in clinical decision-making by providing a stratification of beneficial therapeutic alternatives individualized to the molecular framework of tumor. Larger prospective studies are warranted to further investigate the impact of profiling guided treatment decisions on patient outcomes.

Abstract Background Early phase clinical trials evaluate the safety and efficacy of new treatments. The exclusion/inclusion criteria in these trials are usually rigorous and may exclude many patients seen in clinical practice. Our objective was to study the comorbidities limiting the participation of patients with breast, colorectal, or lung cancer in clinical trials. Materials and Methods We queried ClinicalTrials.gov on December 31, 2016. We reviewed the eligibility criteria of 1,103 trials. Logistic regression analyses were completed, and exclusion was studied as a binary variable. Results Out of 1,103 trials, 70 trials (6%) excluded patients &gt;75 years of age, and 45% made no reference to age. Eighty-six percent of trials placed restrictions on patients with history of prior malignancies. Regarding central nervous system (CNS) metastasis, 416 trials (38%) excluded all patients with CNS metastasis, and 373 (34%) only allowed asymptomatic CNS metastasis. Regarding chronic viral infections, 347 trials (31%) excluded all patients with human immunodeficiency virus, and 228 trials (21%) excluded all patients with hepatitis B or C infection. On univariate analysis, chemotherapy trials were more likely to exclude patients with CNS metastasis and history of other malignancies than targeted therapy trials. Multivariate analysis demonstrated that industry-sponsored trials had higher odds of excluding patients with compromised liver function. Conclusion Many clinical trials excluded large segments of the population of patients with cancer. Frequent exclusion criteria included patients with CNS metastasis, history of prior malignancies, and chronic viral infections. The criteria for participation in some clinical trials may be overly restrictive and limit enrollment. Implications for Practice The results of this study revealed that most early phase clinic trials contain strict exclusion criteria, potentially excluding the patients who may be more likely to represent the population treated in clinical settings, leaving patients susceptible to unintended harm from inappropriate generalization of trial results. Careful liberalization of the inclusion/exclusion criteria in clinical trials will allow investigators to understand the benefits and drawbacks of the experimental drug for a broader population, and possibly improve recruitment of patients with cancer into clinical trials.

e19525 Background: Rearrangements of the immunoglobulin heavy chain (IGH) on chromosome 14 are identified by FISH in about 15-20% of patients (pts) with newly diagnosed multiple myeloma (MM). Historically there is variation on the significance on prognosis of these rearrangements: typically, t(4;14), t(14;16) and t(14;20) have high risk (HR), and t(11;14) have standard risk (SR). A recent study (Kaufman et al, Leukemia. 2016 30:633-9) suggests that t(11;14) may confer a worse prognosis We report the prognostic significance of t(11;14) in a single-institution MM cohort. Methods: 87 pts with t(11;14) by CD 138 selected FISH at diagnosis were identified, pts without symptomatic MM were excluded. Cox regression was used for statistical analysis. Progression free survival (PFS), and overall survivals (OS) from diagnosis and post autologous stem cell transplant (ASCT) were analyzed by Kaplan-Meier. Results: Median age at diagnosis was 62 years, 45 pts (52%) were male, and 24 pts (27%) had ISS 3. All pts received either a proteasome inhibitor or an immunomodulatory agent, and 42 (48%) received triplet treatment as induction. Sixty-nine (79%) pts had ASCT, and overall response rate (ORR, partial response or better) post ASCT was 73%. For pts with HR FISH (defined as t(14;16), p53 del, 1q21 gain or 1p del) compared to SR FISH, the ORR post ASCT was 70% vs 77% (p = 0.67). OS from diagnosis was 93% at 3 years, 74% at 4 years and 51% at 5 years. Seven patients (8%) developed plasma cell leukemia, and there was no association between HR and SR FISH (p = 0.66). In multivariate analysis, ISS stage was an independent risk factor for mortality; pts with stage 3 had 7.3 times (CI: 1.16-36.4) and 5.7 times (CI: 1.63-20.0) the risk of mortality than pts with stage 1 and 2. Having an ASCT reduced mortality by 87% (CI: 0.04-0.41). Conclusions: Despite the use of novel therapies the OS at 5 years of our pts with MM was not significantly improved compared to SEER data from 1992-2013 (51% vs 48.5%). Pts with t(11;14) who had ASCT had increased survival compared to those who did not. Our results suggest that t(11;14) may confer a worse prognosis. Further prospective studies evaluating the risk of t(11;14) are warranted.

8044 Background: Racial disparities of FISH abnormalities in multiple myeloma (MM) have been well described in whites (W) but partially described in minorities (M) (Paulus et al, ASH 2016, 4432). We aimed to explore racial-based differences of FISH abnormalities using the largest cohort of m to date. Methods: CD-138 selected FISH was done on 799 consecutive patients (pts). Pts without symptomatic MM, and biopsy >6 months after diagnosis were excluded. The abnormalities evaluated included standard and intermediate risk: IGH rearrangements (IGH r), t(4;14), t(11;14), and high risk: t(14;20), t(14;16), del13q, del 17p, 1q21. Chi-square was used for statistical analysis. Due to smaller numbers, all m (Hispanic (H), Black (B), Asian (A) and Other (O)) were included into the same group for statistical analysis. Results: 482 pts were eligible, 343 (71%) were W, 52 (10%) H, 50 (10%) B, 19 (3%) A, and 18 (3%) O. Median age was 65 years, 54% were male, and 26% ISS stage 3. There were no were no statistically significant differences in FISH abnormalities between the m (Table1). Overall W had more abnormalities in IGH r, t(4;14), t(11;14), t(14:20), 1q21 gain compared to M. Most notably W had more IGH r (39% vs 28%; p=0.019) and t(11;14) (20% vs 12%; p=0.024). There were no statistically significant differences between W and m in the high risk FISH abnormalities. Conclusions: We had significant differences in FISH compared to M. W had more IGH r and t(11;14) than M, and there was no difference in high risk FISH abnormalities between W and M. This study confirms the biological racial disparities that exist in minorities with MM. Further studies with more inclusion of minorities are needed to elucidate these disparities and its effects on risk stratification and outcomes. [Table: see text]

e15722 Background: Pancreatic cancer (PaCa) is a highly lethal disease, with a 5-year overall survival (OS) rate of approximately 6%, and a median OS of only 3–6 months (m). Despite recent improvements in surgical techniques and increased use of combination chemotherapy (CT), OS remains poor. This study aims to examine the factors that led to increased OS in PaCa patients (pts) over the past two decades in a single academic institution. Methods: All medical records of pts diagnosed with PaCa at the John Theurer Cancer Center from 1990 to 2012 were reviewed, and 916 PaCa pts were included in this analysis. We compared one group of pts diagnosed from 1990 to 2003 (G1, n = 482), with a group of pts diagnosed from 2004 to 2012 (G2, n = 434) in terms of OS, demographics, tumor features and treatment (tx). Results: Median age at diagnosis was 70.5 years (range 26-96). There was no significant difference between G1 and G2 in terms of age at diagnosis, stage of disease and number of pts who received surgery. A significantly higher percentage of pts received CT in G2 compared to G1 (66.5% vs 51.0%, p = .00). Tumors of the pancreatic head were more common in G1 compared to G2 (51.8% vs 44.4% p = .02). More pts in G2 received two or more CT agents compared to G1 (49.0% vs 34.1%, p = .00). Median OS was significantly longer in G2 compared to G1 (9m vs 5m, p = .00), in pts who received CT compared to pts who did not (3m vs 9m, p = .00) and in pts who received surgery compared to pts who did not (5m vs 19m, p = .00). Pancreatic head location was associated with improved OS compared to other locations (9m vs 5m, p = .00). No OS difference was found between pts who received combination with two or more agents vs single agent CT. Conclusions: In line with multiple studies, analysis of PaCa data from our institution showed an increase OS in pts diagnosed with PaCa in more recent years, and in those who received surgery and CT. CT was administered in a larger number of pts in G2, which might account for the better OS in this group. Pts diagnosed with tumors of the pancreatic head had better survival, which could be explained by earlier presentation leading to earlier diagnosis and tx. Further research in PaCa therapeutics is needed, as long-term OS in PaCa pts remains poor despite recent advances.

93 Background: Tumor mutational load (TML) has been proposed as a biomarker of responsiveness to novel immune checkpoint inhibitors (ICIs) due its association with increased neoantigen formation and tumor immunogenicity. Gastrointestinal cancers (GICs) are generally insensitive to ICIs; therefore the aim of this study was to evaluate the TML, clinically relevant genomic alterations (CRGAs), and PDL-1 status of GIC patients (pts). Methods: We analyzed samples of pts with GICs using a multiplatform profiling tool (Caris Life Sciences, Phoenix, AZ). TML and CRGAs were calculated based on next generation sequencing and mutational load was stratified as high (≥17 mut/Mb), intermediate (8-16 mut/Mb), and low (≤ 7 mut/Mb). PD-L1 status was determined by IHC. Descriptive statistics and simple linear regression were used for analysis. Results: A total of 85 pts with GICs were analyzed. The median pt age was 65. 53% were males and 47% were females. Tumors were colorectal 51%, pancreatic 13%, esophageal 13%, gastric 9%, hepatobiliary 11%, anal canal 4%, and small intestine 1%. 80 cases (94%) had an adequate sample for profiling and TML was available in 59 cases (74%). Cases were 5% TML-high, 56% TML-intermediate, and 39% TML-low. The median TML was 9 mut/Mb and median CRGAs was 3. The most commonly detected CRGAs were TP53 (56%), APC (44%), KRAS (40%), ATM (18%) and PTEN (6%). A positive but very weak correlation was found between TML and number of CRGAs (R2 = 0.3). PD-L1 status was available in 74 cases (93%) with 86% being PD-L1 negative and 14% PD-L1 positive. PD-L1 expression was most commonly seen in esophageal (50%) and anal canal (30%) cancers. Among 57 tumors tested for both biomarkers, no correlation was found between a high TML and PD-L1 expression. Conclusions: TML varies among GICs, and higher TML scores were not associated with PD-L1 expression, but there was a weak correlation between TML and the number of CRGAs. Further analysis by stratification of GIC type and prognostic analysis to assess the correlation between TMB and response to ICIs is warranted.